An Introduction to MultiAgent Systems.

http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

IoT security: Review, blockchain solutions, and open challenges

Review: Intrusion detection system: A comprehensive review

Mobile Adhoc Network (MANET) is highly vulnerable to malicious attacks due to infrastructure less network environment, be deficient in centralized authorization. The fact that security is a critical problem when implementing mobile ad hoc networks (MANETs) is widely acknowledged. One of the different kinds of misbehavior a node may exhibit is selfishness. Routing protocol plays a crucial role for effective communication between mobile nodes and operates on the basic assumption that nodes are fully cooperative. Because of open structure and limited battery-based energy some nodes (i.e. selfish or malicious) may not cooperate correctly. There can be two types of selfish attacks –selfish node attack (saving own resources) and sleep deprivation (exhaust others’ resources. In this paper, we propose a new Mobile Agent Based Intrusion Detection System (IDS). The approach uses a set of Mobile Agent (MA) that can move from one node to another node within a network. This as a whole reduces network bandwidth consumption by moving the computation for data analysis to the location of the intrusion. Besides, it has been established that the proposed method also decreases the computation overhead in each node in the network.

Detection of Denial of Service Attack Due to Selfish Node in MANET by Mobile Agent

Abstract In this paper we propose a novel algorithm CLAR to build an agent based routing protocol using ACO technique in cluster based mobile ad-hoc networks. Clustering makes possible hierarchical routing in which paths are recorded between cluster-heads instead of nodes. This reduces routing overheads. Presence of an unstable and non-reliable cluster-head degrades the performance of the network since cluster-heads of the network take active role in routing messages between a source destination pair. The proposed algorithm chooses the most reliable and stable node as cluster-head depending on four criteria i.e.: stability, battery power, degree, and trust value of the node. It also uses a multiagent based routing algorithm to generate load balanced routes between source and destination in cluster-based network. Performance of CLAR is compared with other existing efficient algorithms such as AODV, CBRP, Wu & Li’s Algorithm, dominating set based clustering algorithms, agent-based algorithms named as SACO and MALBACO. Simulation results prove that the proposed protocol combines merits of both clustering approach and agent based approach and provides efficient packet delivery even in the presence of high load in the network

/pdf/clar-a-novel-cluster-oriented-agent-based-routing-protocol-1r718clunq.pdf

Clar: A Novel Cluster Oriented Agent Based Routing Protocol for Manet

New Database Architecture for Smart Query Handler of Spatial Database

Accurate segmentation and delineation of the sub-tumor regions are very challenging tasks due to the nature of the tumor. Traditionally, convolutional neural networks (CNNs) have succeeded in achieving most promising performance for the segmentation of brain tumor; however, handcrafted features remain very important in identification of tumor’s boundary regions accurately. The present work proposes a robust deep learning–based model with three different CNN architectures along with pre-defined handcrafted features for brain tumor segmentation, mainly to find out more prominent boundaries of the core and enhanced tumor regions. Generally, automatic CNN architecture does not use the pre-defined handcrafted features because it extracts the features automatically. In this present work, several pre-defined handcrafted features are computed from four MRI modalities (T2, FLAIR, T1c, and T1) with the help of additional handcrafted masks according to user interest and fed to the convolutional features (automatic features) to improve the overall performance of the proposed CNN model for tumor segmentation. Multi-pathway CNN is explored in this present work along with single-pathway CNN, which extracts simultaneously both local and global features to identify the accurate sub-regions of the tumor with the help of handcrafted features. The present work uses a cascaded CNN architecture, where the outcome of a CNN is considered as an additional input information to next subsequent CNNs. To extract the handcrafted features, convolutional operation was applied on the four MRI modalities with the help of several pre-defined masks to produce a predefined set of handcrafted features. The present work also investigates the usefulness of intensity normalization and data augmentation in pre-processing stage in order to handle the difficulties related to the imbalance of tumor labels. The proposed method is experimented on the BraST 2018 datasets and achieved promising results than the existing (currently published) methods with respect to different metrics such as specificity, sensitivity, and dice similarity coefficient (DSC) for complete, core, and enhanced tumor regions. Quantitatively, a notable gain is achieved around the boundaries of the sub-tumor regions using the proposed two-pathway CNN along with the handcrafted features.

An efficient brain tumor image classifier by combining multi-pathway cascaded deep neural network and handcrafted features in MR images.

Security and privacy are one of the most challenging issues related to the deployment of the Vehicular Ad hoc Networks. Different security proposals have been introduced to address the security of the data those are reliant on the centralized architecture based solutions along with the popular hardware based security techniques. In this proposal the existing state-of-the-art diverse security based solutions have analyzed which leads to the research gap analysis. Authors have presented new secure certificate based scheme to address several obtainable problems. We have proposed a hierarchical architecture for VANET. This proposal deals with the certificate based authentication mechanism which is executed on user request. The unique message identifier technique has taken a pivot role for avoiding the message deception. The proposed SBRPV technique is used to accomplish privacy and traceability, besides, satisfying elementary security requirements.

Rituparna Chaki

Papers

Detection of Denial of Service Attack Due to Selfish Node in MANET by Mobile Agent

Clar: A Novel Cluster Oriented Agent Based Routing Protocol for Manet

New Database Architecture for Smart Query Handler of Spatial Database

An efficient brain tumor image classifier by combining multi-pathway cascaded deep neural network and handcrafted features in MR images.

SBRPV: Security Based Routing Protocol for Vehicular Ad hoc Networks